AIoT: The powerful convergence of AI and the IoT

Dinesh Soundararajan of Contus

From fictional characters like Joey and Phoebe in Friends to the hamburger & fries combo for foodies, the greatest and most powerful duos have existed throughout the history of mankind. They may have a unique individuality but when clubbed together boom! Together, says Dinesh Soundararajan of Contus, they create an awesome and wonderful impact.

Similarly, the perfect amalgamation of the Internet of Things (IoT) with Artificial Intelligence (AI), together known as AIoT, is all geared up to give enterprises the best of both worlds! This is backed up with recent research from which states that by 2023, the global value of IoT in embedded IoT devices market will grow to US$26.2 billion (€23.9 b illion)

AIoT gives a competitive edge to IoT technologies

AIoT in simple terms means to make the Internet of Things perform intelligence tasks with the help of integrating Artificial Intelligence.”

The Artificial Internet of Things helps to connect IoT devices with sensors that are integrated

with AI capabilities – all of these with no human intervention.

Key factors of Artificial Internet of Things

That being said, let’s see how these Artificial Internet of Things actually help the business world move towards a next-gen transformation.

How does AIoT differ from IoT?

Are you wondering why we need AIoT when the Internet of Things market is doing well across several industries? Well, here is a quick look at the differences between these two technologies. We can call AIoT the next version of IoT.

IoT IoT is like the digital nervous system Internet of Things requires hardware sensors to be physically attached to the machines to retrieve data IoT requires minimal human intervention Industrial IoT devices collect millions of data sets from various equipment but they don’t do any analysis. AIoT AIoT is the brain that controls the nervous system, to make better business decisions AIoT, which provides intelligent decision-making, requires software code developed by the programmers to perform certain tasks AIoT, the next logical step of the Internet of Things, is primarily designed to work independently with no human support With the use of AI algorithms and predictive maintenance implemented in IIoT, self-healing IoT devices with data analytics are created to make better decision-making.

Benefits of AIoT to shape the future of your business model

“ In this era of 5G, the AIoT technology will only be enhanced further where it will connect every object, people, and machines in a more meaningful way.”

Having an intertwined relationship between IoT and AI will help organisations move to the next level. Now that AI and IoT have individually marked their presence in the digital world, many IoT app development companies are moving towards AIoT for managing Internet of Things connected devices with artificial intelligence techniques.

AIoT based on the business perspective

Let’s look at the advantages of AIoT for business:

➔ Intelligent business decisions

The data collected from millions of IoT devices is so massive it makes it difficult to segregate and extract useful information from it. To organise these unstructured data into a meaningful chuck of data, AI-based algorithms are used to eliminate junk data and leverage any business model.

Now the chief technology officers (CTOs) and other decision-makers can make firm business decisions based on the valuable insights retrieved from this data.

➔ Enhanced operational efficiency

Smart automation surpasses the traditional approach by streamlining the organisation’s processes. Several industries have implemented these AIoT technologies to save on resources. For example, in office buildings, smart environmental sensors provide data on how many people are safe inside the premises. This includes fire, theft or any other warnings.

The integration of human facial recognition software and other biometric access devices all facilitate remote monitoring of the physical security of office buildings. Any unidentified personnel or abnormal activities are swiftly recorded and alerts or notifications can be sent automatically to the central hub.

AIoT based on the customer perspective

Let’s briefly look into the advantages of AIoT for customers:

➔ Delightful customer experiences

Understand your customer’s behaviour and their challenges more precisely with Artificial Internet of Things technology. For instance, the surveillance camera is not only used to detect any thefts or crime, it also helps to read the customer’s shopping pattern.

AIoT collects and correlates inventory data, such as which aisle needs re-filling fast or where goods are fast-moving, and which aisle has seen no customer visits at all. Hence, large organisations are able to predict the customer’s habits more accurately and make it a more personalised experience for them.

➔ Accurate predictions

Artificial Internet of Things provides next-level predictions to get accurate results. One of the powerful use cases of AIoT is the autonomous robot used for delivery. The robots have in-built sensors that collect and store data retrieved from the IoT devices. It stores data like physical addresses, direction details, and traffic information.

After collecting the data, the AI fed into the robot system detects less congested routes and makes a smart decision by detouring to routes where there is less traffic. Then, it delivers the package to the relevant address.

Several other industries have been implementing IoT data visualisation techniques. These include office buildings with smart environmental sensors and facial recognition software to get real-time data and behavioural analysis.

Practical applications of AIoT

DHL – A leading global logistics company

“By 2028, DHL aims to build 10,000 IoT-enabled truck transportation vehicles. It says AIoT has reduced 50% of their transit time with 90% reliability of real-time tracking.”

DHL leverages the innovative IoT solutions along with artificial intelligence through Smart Trucking operations teams using an agile model where it streamlines the businesses by creating a transportation model that decreases the fatigue among the drivers, and helps them to spend less time on the road and provide a better work-life balance.

Board member of DHL, Juergen Gerdes said in an interview, “We expect to transport 100,000 tonnes of cargo and plan to cover 4 million kilometres daily worldwide.”

WalMart – The largest retail chain in North America

With more than 11,000 brick and mortar models with equally numerous online stores for each county or state, Walmart was able to pull it off effortlessly with the help of AI and machine learning (ML) integrated with the Internet of Things.

Facial recognition software, voice-based search by Google Assistant and cross-technology solutions, have made this retail industry scale up to higher revenues for several years.

London City Airport – travel & leisure industry

London City Airport was the first airport to make use of AI, the Internet of Things and cross-technology networking to monitor every tiny detail of travel to provide the passengers with informed data.

Cabin crew can now track the whereabouts of the passengers through IoT devices, boarding queue traffic, can update gate information, track baggage and so on.

Right from Industrial IoT (IIoT) protocols & Constrained Application Protocol (CoAP) to Web Socket & application program interfaces (APIs), Contus has a solid IoT/IIoT Digital Engine model. Along with the Business Intelligence solutions and IoT dashboard it helps to accelerate the business delivery process effectively.

We help in leveraging the industry-focused IoT App development solutions in a cost-effective way.

Wrapping Up

IoT with artificial intelligence has vast use cases across industries, and it is purely dependent upon the organisation’s budget and goals to align them perfectly to increase their productivity. These are one-time investments that will yield them a life-long benefit. Get detailed analytics, precise data processing, and automation techniques all in one place, all built basically to give better results from bigger and meaningful data.

Abouth the author

The author is Dinesh Soundararajan, co-founder and director for IoT & IIoT Solutions at Contus. His work experience spans spearheading tech product engineering, solution deliveries and quality assurance grounded on SMAC technologies. You can find him at:

Comment on this article below or via Twitter: @IoTNow_OR @jcIoTnow


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